Instances of the article: "Scheduling personalized study plans considering the stress factor"

Instances of the article: "Scheduling personalized study plans considering the stress factor" The educational planning problem generates personalized learning paths for students by scheduling activities necessary to satisfy an expected grade, which minimizes the total duration of activities belonging to this learning path by considering the stress and the student's learning capacity. We propose two scheduling models with two new activity duration functions incorporating stress and sequence dependence to mimic learning effects. We also propose a metaheuristic to solve real-size instances, which is composed of a greedy randomized adaptive search procedure enhanced by a variable neighborhood search. Experimental results validate the efficiency of our approach.

本数据集的实例源自论文《考虑压力因素的个性化学习计划调度》。教育规划问题通过调度满足预期学业成绩所需的各项学习活动，为学生生成个性化学习路径，并通过考量学习压力与学生学习能力，最小化该学习路径下所有活动的总耗时。本文提出两类调度模型，构建两种融入压力与序列依赖性的新型活动时长函数以模拟学习效应。此外，本文提出一种元启发式算法以求解实际规模的实例，该算法由经变邻域搜索（Variable Neighborhood Search）增强的贪婪随机自适应搜索算法（Greedy Randomized Adaptive Search Procedure）构成。实验结果验证了所提方法的有效性。